• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.766-772
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• 1999

With the increase of portable system and high-density IC, power consumption of VLSI circuits is very important factor in design process. Power estimation is required in order to estimate the power consumption. A simple and correct solution of power estimation is to use circuit simulation. But it is very time consuming and inefficient way. Probabilistic method has been proposed to overcome this problem. Transition density using probability was an efficient method to estimate power consumption using BDD and Boolean difference. But it is difficult to build the BDD and compute complex Boolean difference. In this paper, we proposed Propowest. Propowest is building a digraph of circuit, and easy and fast in computing transition density by using modified COP algorithm. Propowest provides an efficient way for power estimation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.2
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• pp.325-328
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• 1996

In this paper, we proposed an estimation method of a posterior probability and PDF(Probability density function) using a feed forward neural network and code books of VQ(vector quantization). In this study, We estimates a posterior probability and probability density function, which compose a new parameter with well-known Mel cepstrum and verificate the performance for the five vowels taking from syllables by NN(neural network) and PNN(probabilistic neural network). In case of new parameter, showed the best result by probabilistic neural network and recognition rates are average 83.02%.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.2
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• pp.70-78
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• 2011

The paper aims at developing a more reliable and accurate BWIM(Bridge Weigh-In-Motion) algorithm using measured strain data and examining its efficiency with various tests on bridges. It proposes a BWIM algorithm using density estimation function and average modification factor for moment-strain relationship. Density estimation function has been proved to be reliably applied when multiple axle loads are estimated. An average modification factor is applied to minimize overall error that can be encountered between theoretically computed moments and measured strains at multiple locations in a bridge. The developed algorithm has been successfully examined through numerical simulations, laboratory tests, and also by field tests on a multi-girder composite bridge.

• Journal of the Korean Statistical Society
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• v.28 no.4
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• pp.443-455
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• 1999

A simulation-based approach to estimating the probability of an arbitrary region under a multivariate normal distribution is developed. In specific, the probability is expressed as the ratio of the unrestricted and the restricted multivariate normal density functions, where the restriction is given by the region whose probability is of interest. The density function of the restricted distribution is then estimated by using a sample generated from the Gibbs sampling algorithm.

• Journal of the Korean Statistical Society
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• v.27 no.1
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• pp.91-100
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• 1998

A method of estimating probability density using regression tools is presented here. It is based on equal-length binning and locally weighted approximate likelihood for bin counts. The method is particularly useful for densities with bounded supports, where it automatically corrects edge effects without using boundary kernels.

• Progress in Superconductivity and Cryogenics
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• v.12 no.3
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• pp.16-20
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• 2010

For large scale power applications of HTS conductor, it is getting more important to have a stacked HTS coated conductor with low loss and large current capacity. But it was not easy to measure some electric properties. Stabilizer free YBCO CC for striated/ stacked conductors is easily burned out during the measurement of the critical current density because it has no stabilizer and it is difficult to set-up the current lead and voltage taps because it has many pieces of YBCO CC in a conductor. Instead of direct measuring the critical current of a stacked HTS coated conductor, indirect estimation from measuring a magnetization loss of HTS coated conductor could be useful for practical estimation of the critical current. The magnetization loss of a superconductor is supposed to be affected by a full penetrating magnetic field, and it tends to show an inflection point at the full penetrating magnetic field when we generate the graph of magnetization loss vs. external magnetic field. The full penetrating magnetic field depends on the shape of the conductor and its critical current density, so we can estimate the effective critical current density from measuring the magnetization loss. In this paper, to prove the effectiveness of this indirect estimation of the critical current, we prepared several different kinds of YBCO CC(coated conductor) including a stacked conductor short samples and measured the magnetization losses and the critical currents of each sample by using linked pick up coils and direct voltage measurement with transport current respectively.

• Journal of Environmental Health Sciences
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• v.34 no.2
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• pp.131-136
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• 2008

The variation of the particle size distribution and density as well as the chemical composition of aerosols is important to evaluate the particles. This study measured and analyzed airborne particles using a scanning mobility particle sizer (SMPS) system and an aerodynamic particle sizer (APS) at the University of Seoul during every season. The highest particle number concentration of airborne particles less than $0.9\;{\mu}m$, occurred in winter, while the highest particle number concentration of airborne particles more than $0.9\;{\mu}m$, occurred in spring. Mass concentration appeared highest at spring. Also, when we compared $\beta$-ray's mass concentration with calculated mass concentration by using the SMPS-APS system during each season, density of the winter is $1.92\;g/cm^3$, spring density is $1.64\;g/cm^3$, fall density is $1.57\;g/cm^3$. We found out that PM10 density was differ every season. However, while the calculated density is whole density for PM10 the density of each diameter was different. In this study the density estimation equation of the QCM cascade impactor measured mass concentration of each diameter.

• The KIPS Transactions:PartA
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• v.9A no.1
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• pp.75-82
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• 2002

A robust signal transition density propagation method for a zero delay model is presented to obtain the signal transition density for estimating the power consumption. The power estimation for the zero delay model is a proper criteria for the lower boundary of power consumption. Since the input characteristics are generally unknown at design stage, robust estimation for wide range input characteristics is very important for the power consumption. In this paper, a conventional transition estimation method will be explored. And this exploration will be analyzed with the input/output signal transition behavior and used to propose the robust signal transition density propagation for the power estimation. In order to apply to practical circuits, the reconvergent path, which is crucial to affect the exactness of the power estimation, will be studied and an algorithm to take the reconvergent path into consideration will be presented. In experiment, the proposed methodology shows better robustness, comparable accuracy and elapsed time compared to the conventional methods.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.669-684
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• 2012

Discrete wavelet transforms are extensively preferred in biomedical signal processing for denoising, feature extraction, and compression. This paper presents a new denoising method based on the modeling of discrete wavelet coefficients of ECG in selected sub-bands with Kernel density estimation. The modeling provides a statistical distribution of information and noise. A Gaussian kernel with bounded support is used for modeling sub-band coefficients and thresholds and is estimated by placing a sliding window on a normalized cumulative density function. We evaluated this approach on offline noisy ECG records from the Cardiovascular Research Centre of the University of Glasgow and on records from the MIT-BIH Arrythmia database. Results show that our proposed technique has a more reliable physical basis and provides improvement in the Signal-to-Noise Ratio (SNR) and Percentage RMS Difference (PRD). The morphological information of ECG signals is found to be unaffected after employing denoising. This is quantified by calculating the mean square error between the feature vectors of original and denoised signal. MSE values are less than 0.05 for most of the cases.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.982-987
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• 2012

In this paper, the SNR estimation error of Decision Directed SNR estimation method in AWGN is investigated, which uses samples received in reference decision region. In communication system receiver, when SNR estimation scheme using error vectors between ideal sample points and received sample points of reference region is adopted, the samples contain incorrectly received samples due to AWGN. Consequently, the mean of estimated reference constellation point is shifted and Decision Directed SNR estimation is inaccurately performed. These effects are explained by modified probability density function and difference between actual SNR and estimated SNR is theoretically derived and quantatively analyzed. It is proved that SNR estimation error obtained through computer simulation is matched up with derived one, and SNR estimation performance is enhanced significantly by adopting suggested correction scheme.